drsmooth-package: drsmooth-package: Dose-response Modeling with Smoothing...
In drsmooth: Dose-Response Modeling with Smoothing Splines

Description Details drsmooth functions See Also

drsmooth provides tools for assessing the shape of a dose-response curve by testing linearity and non-linearity at user-defined cut-offs. It also provides two methods of estimating a threshold dose, or the dose at which the dose-response function transitions to significantly increasing: bi-linear (based on pkg:segmented) and smoothed with splines (based on pkg:mgcv).

v.1.9.0 introduces spline-based dose-response modeling on dichotomous data, with examples using the included DIdata. See NEWS for details, as well as the help files for the exported functions itemized below.

There are 8 user-initiated functions in this package; see the help pages for documentation of each.

prelimstats() executes up to 5 tests of homogeneity & normality.

noel() executes up to 5 tests to determine the no-observed-effect-level.

nlaad(), lbcd(), nlbcd() test linearity across all doses, linearity below a defined cut-off dose, and non-linearity below a defined cut-off dose, respectively.

spline.plot() only prints the smoothed dose-response curve.

segment() returns a two-segment linear dose-response model, by imposing a zero slope for the initial (left) segment and detecting one breakpoint where the dose-response relation changes to a positive slope (if such a breakpoint exists).

drsmooth() generates a spline model with the input dose and response, plots the spline-estimated dose-response function with its upper and lower 95 percent confidence bounds along with the actual data, and returns key metrics related to the dose-response function.

expand () expands summarized dichotomous data into the format expected by drsmooth(), if needed.

drsmooth

drsmooth documentation built on May 1, 2019, 10:28 p.m.